Hierarchical algorithms for discounted and weighted Markov decision processes

We consider a discrete time finite Markov decision process (MDP) with the discounted and weighted reward optimality criteria. In [1] the authors considered some decomposition of limiting average MDPs. In this paper, we use an analogous approach for discounted and weighted MDPs. Then, we construct some hierarchical decomposition algorithms for both discounted and weighted MDPs. Copyright Springer-Verlag 2003

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Year of publication:	2003
Authors:	Abbad, M. ; Daoui, C.
Published in:	Computational Statistics. - Springer. - Vol. 58.2003, 2, p. 237-245
Publisher:	Springer
Subject:	Discounted MDP \| Weighted MDP \| Decomposition \| Strongly Connected Classes \| Graph theory

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010759229